tt = np.linspace(0, 32*10/1600, 32*10, endpoint=False)
# A phase comparison vector. This should be the idea output.
pt = np.concatenate((((2*np.pi*50.0*tt+np.pi) % (2*np.pi) - np.pi),(2*np.pi*ft*tt+np.pi) % (2*np.pi) - np.pi))
# The test input vector
yt = np.concatenate((mag*np.cos(2*np.pi*50*tt) + dc_offset, mag*np.cos(2*np.pi*ft*tt) + dc_offset))
# Re-define tt to extend the full length.
tt = np.linspace(0, 2*32*10/1600, 2*32*10, endpoint=False)
step_time = (32*10)/1600 # used for drawing a line of the plots
# Create and run the filter, noting increasing the number of iterations
# will reduce the LES filter settling time at the cost of higher computation time.
les = LES(iterations=1)
les_out = les.run_les(yt)
# Visualisation of the output
fig, ((ax1, ax2), (ax3, ax4)) = plt.subplots(2, 2, sharex=True, sharey=False)
fig.suptitle('LES Freq Step Test', fontsize=16)
# Plots have the LES generated lines wider so the correct lines is overlayed and visable.
# Plot the phases
ax1.plot(tt, les_out[1], linewidth=3)
ax1.plot(tt, pt)
ax1.set_title('Phase (rad)')
ax1.axvline(x=step_time, ls='--', c='red')
# Plot the freqency
ax2.plot(tt, les_out[2], linewidth=3)
